In modern retail market, electronic commerce has rapidly gained a lot of attention and also provides instantaneous transactions. In electronic commerce, credit card has become the most important means of payment due to fast development in information technology around the world. The objective of the paper is to develop a credit card fraud detection system in commercial sites. It is designed as a web based application in which transition state model was adopted for the research process. PHP (Hypertext Pre-Processor) is used for application development and MySQL to generate databases. The result shows that the system performance is performing to its task and therefore recommended to electronic commerce owners to ensure data integrity and security of their customers.
R.J. Baton and D. J. Hand (2002). A review on statistical fraud detection: statistical science. International Journal of Science and Technology. Volume 17, issue I, pp 15.
T.P. Bhatla, V. Prabhu and A. Dua, (2003). Understanding credit card frauds: a review on card Business.Pp 20.
D. Kayong, Z. Ru and G. Hong (2012). Analysis and study of detection of credit card fraud in E-commerce. Vol.13 pg 12-17
M. S. Khan and S. S. Mahaptra (2011). Service quality evaluation in internet banking website quality in India: A webqual approach great lakes herald pg 40-58
Paterson, Ken, Credit card issuer fraud management, report highlights. Mercator Advisory Group. Archived from the original (PDF) December 2008
Hassibi, Khosrow, Detection payment card fraud with neural networks in book. Business Applications of neural networks, Singapore-New Jersey-London-Hong Kong: World Scientific, 2000, pp. 141–158.
Court filings double estimate of TJX breach 2007
V. Dheepa and R. Dhanapal R. (2009.) Analysis of Credit Card Fraud Detection Methods
Dahee Choi and Kyungho Lee (2018). An Artificial Intelligence Approach to Financial Fraud Detection under IoT Environment: A Survey and Implementation.
L. Delamaire, Hussein A. Abdou and John Pointon (2009). Credit card fraud and detection techniques: A review
G. C. Alex, de Sa, C. M. Adriaono, Pereira Gisele L., Pappa (2018) A customized classification algorithm for credit card fraud detection. Engineering Applications of Artificial Intelligence. Published by Elsevier. Volume 72, pages 21-29
Masoumeh Zareapoor and Pourya Shamsolmoali (2015). Application of Credit Card Fraud Detection: Based on Bagging Ensemble Classifier. International Conference on Artificial Intelligent Computing, Communication and Convergence. Procedia Computer Science. Volume 48, pages 679-685
John O Awoyemi, Adebayo O. Adetunmbi and Samuel A. Oluwadare (2017). Credit card fraud detection using machine learning techniques: A comparative analysis. International Conference on Computing Network and Informatics (ICCNI)
D. K. Gangeshwer (2005). E-Commerce or Internet Marketing: A Business Review from Indian Context. International Journal of u- and e- Service, Science and Technology Vol.6, No.6 (2013), pp.187-194. http://dx.doi.org/10.14257/ijunesst.2013.6.6.17
Nuno Carneiro, Goncalo Figueira and MiguelCosta (2017). A data mining based system for credit-card fraud detection in e-tail. Decision Support Systems. Volume 95 March 2017, Pages 91-101
Stephen Whitworth. What kind of statistical methods are used in credit card fraud detection and anti-money laundering. February 23, 2016.
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